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<h1>Welcome to ScoreCardModel’s documentation!<a class="headerlink" href="#welcome-to-scorecardmodel-s-documentation" title="Permalink to this headline">¶</a></h1>
<ul class="simple">
<li>version: 1.1.2</li>
<li>status: dev</li>
<li>author: hsz</li>
<li>email: <a class="reference external" href="mailto:hsz1273327&#37;&#52;&#48;gmail&#46;com">hsz1273327<span>&#64;</span>gmail<span>&#46;</span>com</a></li>
</ul>
<div class="section" id="desc">
<h2>Desc<a class="headerlink" href="#desc" title="Permalink to this headline">¶</a></h2>
<p>a simple tool for score card model</p>
<p>keywords:math,finance</p>
</div>
<div class="section" id="feature">
<h2>Feature<a class="headerlink" href="#feature" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li>Serializable</li>
<li>mutil classifier model support</li>
<li>ks-curve support</li>
</ul>
</div>
<div class="section" id="change">
<h2>Change<a class="headerlink" href="#change" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li>scorecard now can set a threshold value to return a bool result</li>
</ul>
</div>
<div class="section" id="example">
<h2>Example<a class="headerlink" href="#example" title="Permalink to this headline">¶</a></h2>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">sklearn</span> <span class="k">import</span> <span class="n">datasets</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ScoreCardModel.binning.discretization</span> <span class="k">import</span> <span class="n">Discretization</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ScoreCardModel.weight_of_evidence</span> <span class="k">import</span> <span class="n">WeightOfEvidence</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ScoreCardModel.models.logistic_regression_model</span> <span class="k">import</span> <span class="n">LogisticRegressionModel</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ScoreCardModel.score_card</span> <span class="k">import</span> <span class="n">ScoreCardModel</span>
<span class="go">&gt;&gt;&gt;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="k">class</span> <span class="nc">MyLR</span><span class="p">(</span><span class="n">LogisticRegressionModel</span><span class="p">):</span>
<span class="gp">&gt;&gt;&gt; </span>    <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
<span class="gp">&gt;&gt;&gt; </span>         <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">pre_trade</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_predict_proba</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="go">&gt;&gt;&gt;</span>
<span class="gp">&gt;&gt;&gt; </span>    <span class="k">def</span> <span class="nf">pre_trade</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="n">result</span> <span class="o">=</span> <span class="p">[]</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="k">for</span> <span class="n">i</span><span class="p">,</span><span class="n">v</span> <span class="ow">in</span> <span class="n">x</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="gp">&gt;&gt;&gt; </span>            <span class="n">t</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">ds</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">transform</span><span class="p">([</span><span class="n">v</span><span class="p">])[</span><span class="mi">0</span><span class="p">]</span>
<span class="gp">&gt;&gt;&gt; </span>            <span class="n">r</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">woes</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">transform</span><span class="p">([</span><span class="n">t</span><span class="p">])[</span><span class="mi">0</span><span class="p">]</span>
<span class="gp">&gt;&gt;&gt; </span>            <span class="n">result</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">r</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">result</span><span class="p">)</span>
<span class="go">&gt;&gt;&gt;</span>
<span class="gp">&gt;&gt;&gt; </span>    <span class="k">def</span> <span class="nf">_pre_trade_batch_row</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">row</span><span class="p">,</span><span class="n">Y</span><span class="p">,</span><span class="n">bins</span><span class="p">):</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="n">d</span> <span class="o">=</span> <span class="n">Discretization</span><span class="p">(</span><span class="n">bins</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="n">d_row</span> <span class="o">=</span> <span class="n">d</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">row</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="n">woe</span> <span class="o">=</span> <span class="n">WeightOfEvidence</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="n">woe</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">d_row</span><span class="p">,</span><span class="n">Y</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="k">return</span> <span class="n">d</span><span class="p">,</span><span class="n">woe</span><span class="p">,</span><span class="n">woe</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">d_row</span><span class="p">)</span>
<span class="go">&gt;&gt;&gt;</span>
<span class="gp">&gt;&gt;&gt; </span>    <span class="k">def</span> <span class="nf">pre_trade_batch</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span><span class="n">Y</span><span class="p">):</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="bp">self</span><span class="o">.</span><span class="n">ds</span> <span class="o">=</span> <span class="p">{}</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="bp">self</span><span class="o">.</span><span class="n">woes</span> <span class="o">=</span> <span class="p">{}</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="bp">self</span><span class="o">.</span><span class="n">table</span> <span class="o">=</span> <span class="p">{}</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="bp">self</span><span class="o">.</span><span class="n">ds</span><span class="p">[</span><span class="s2">&quot;sepal length (cm)&quot;</span><span class="p">],</span><span class="bp">self</span><span class="o">.</span><span class="n">woes</span><span class="p">[</span><span class="s2">&quot;sepal length (cm)&quot;</span><span class="p">],</span><span class="bp">self</span><span class="o">.</span><span class="n">table</span><span class="p">[</span><span class="s2">&quot;sepal length (cm)&quot;</span><span class="p">]</span><span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_pre_trade_batch_row</span><span class="p">(</span>
<span class="gp">&gt;&gt;&gt; </span>            <span class="n">X</span><span class="p">[</span><span class="s2">&quot;sepal length (cm)&quot;</span><span class="p">],</span><span class="n">Y</span><span class="p">,[</span><span class="mi">0</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">8</span><span class="p">])</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="bp">self</span><span class="o">.</span><span class="n">ds</span><span class="p">[</span><span class="s1">&#39;sepal width (cm)&#39;</span><span class="p">],</span><span class="bp">self</span><span class="o">.</span><span class="n">woes</span><span class="p">[</span><span class="s1">&#39;sepal width (cm)&#39;</span><span class="p">],</span><span class="bp">self</span><span class="o">.</span><span class="n">table</span><span class="p">[</span><span class="s1">&#39;sepal width (cm)&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_pre_trade_batch_row</span><span class="p">(</span>
<span class="gp">&gt;&gt;&gt; </span>            <span class="n">X</span><span class="p">[</span><span class="s1">&#39;sepal width (cm)&#39;</span><span class="p">],</span><span class="n">Y</span><span class="p">,[</span><span class="mi">0</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mf">2.5</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mf">3.5</span><span class="p">,</span><span class="mi">5</span><span class="p">])</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="bp">self</span><span class="o">.</span><span class="n">ds</span><span class="p">[</span><span class="s1">&#39;petal length (cm)&#39;</span><span class="p">],</span><span class="bp">self</span><span class="o">.</span><span class="n">woes</span><span class="p">[</span><span class="s1">&#39;petal length (cm)&#39;</span><span class="p">],</span><span class="bp">self</span><span class="o">.</span><span class="n">table</span><span class="p">[</span><span class="s1">&#39;petal length (cm)&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_pre_trade_batch_row</span><span class="p">(</span>
<span class="gp">&gt;&gt;&gt; </span>            <span class="n">X</span><span class="p">[</span><span class="s1">&#39;petal length (cm)&#39;</span><span class="p">],</span><span class="n">Y</span><span class="p">,[</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">7</span><span class="p">])</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="bp">self</span><span class="o">.</span><span class="n">ds</span><span class="p">[</span><span class="s1">&#39;petal width (cm)&#39;</span><span class="p">],</span><span class="bp">self</span><span class="o">.</span><span class="n">woes</span><span class="p">[</span><span class="s1">&#39;petal width (cm)&#39;</span><span class="p">],</span><span class="bp">self</span><span class="o">.</span><span class="n">table</span><span class="p">[</span><span class="s1">&#39;petal width (cm)&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_pre_trade_batch_row</span><span class="p">(</span>
<span class="gp">&gt;&gt;&gt; </span>            <span class="n">X</span><span class="p">[</span><span class="s1">&#39;petal width (cm)&#39;</span><span class="p">],</span><span class="n">Y</span><span class="p">,[</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">])</span>
<span class="gp">&gt;&gt;&gt; </span>        <span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">table</span><span class="p">)</span>
<span class="go">&gt;&gt;&gt;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">iris</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">load_iris</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">iris</span><span class="o">.</span><span class="n">target</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">z</span> <span class="o">=</span> <span class="p">(</span><span class="n">y</span><span class="o">==</span><span class="mi">0</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">l</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">iris</span><span class="o">.</span><span class="n">data</span><span class="p">,</span><span class="n">columns</span><span class="o">=</span><span class="n">iris</span><span class="o">.</span><span class="n">feature_names</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">lr</span> <span class="o">=</span> <span class="n">MyLR</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">lr</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">l</span><span class="p">,</span><span class="n">z</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">lr</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">l</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">to_dict</span><span class="p">())</span>
<span class="go">array([[ 0.46315882,  0.53684118]])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">sc</span> <span class="o">=</span> <span class="n">ScoreCardModel</span><span class="p">(</span><span class="n">lr</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">sc</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">sc</span><span class="o">.</span><span class="n">pre_trade</span><span class="p">(</span><span class="n">l</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">to_dict</span><span class="p">()))</span>
<span class="go">104.3</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">scs</span> <span class="o">=</span> <span class="p">[]</span>
<span class="gp">&gt;&gt;&gt; </span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">l</span><span class="p">)):</span>
<span class="gp">&gt;&gt;&gt; </span>   <span class="n">score</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">sc</span><span class="o">.</span><span class="n">pre_trade</span><span class="p">(</span><span class="n">l</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">to_dict</span><span class="p">()))</span>
<span class="gp">&gt;&gt;&gt; </span>   <span class="n">scs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">score</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">ScoreCardWithKSModel</span><span class="o">.</span><span class="n">Threshold_to_score</span><span class="p">(</span><span class="n">scs</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">))</span>
<span class="go">1.0</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">ScoreCardWithKSModel</span><span class="o">.</span><span class="n">Score_to_threshold</span><span class="p">(</span><span class="n">scs</span><span class="p">,</span> <span class="n">score</span><span class="o">=</span><span class="mi">70</span><span class="p">))</span>
<span class="go">1.0</span>
<span class="go">.</span>
<span class="go">.</span>
<span class="go">.</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">ScoreCardWithKSModel</span><span class="o">.</span><span class="n">Score_to_threshold</span><span class="p">(</span><span class="n">scs</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="n">z</span><span class="p">,</span> <span class="n">score</span><span class="o">=</span><span class="mi">100</span><span class="p">))</span>
<span class="go">0.3467</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">ScoreCardWithKSModel</span><span class="o">.</span><span class="n">Get_ks</span><span class="p">(</span><span class="n">scs</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="n">z</span><span class="p">,</span> <span class="n">threshold</span><span class="o">=</span><span class="mf">0.4</span><span class="p">)</span><span class="o">.</span><span class="n">ks</span><span class="p">)</span>
<span class="go">0.9</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># ScoreCardWithKSModel.Drawks(scs, y=z)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">scsc</span> <span class="o">=</span> <span class="p">[</span><span class="n">l</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">to_dict</span><span class="p">()</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">l</span><span class="p">))]</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">scks</span> <span class="o">=</span> <span class="n">ScoreCardWithKSModel</span><span class="o">.</span><span class="n">From_scorecard</span><span class="p">(</span><span class="n">sc</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">scks</span><span class="o">.</span><span class="n">threshold_to_score</span><span class="p">(</span><span class="n">scsc</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">))</span>
<span class="go">1.0</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">scks</span><span class="o">.</span><span class="n">score_to_threshold</span><span class="p">(</span><span class="n">scsc</span><span class="p">,</span> <span class="n">score</span><span class="o">=</span><span class="mi">70</span><span class="p">))</span>
<span class="go">1.0</span>
<span class="go">.</span>
<span class="go">.</span>
<span class="go">.</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">scks</span><span class="o">.</span><span class="n">score_to_threshold</span><span class="p">(</span><span class="n">scsc</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="n">z</span><span class="p">,</span> <span class="n">score</span><span class="o">=</span><span class="mi">100</span><span class="p">))</span>
<span class="go">0.3467</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">scks</span><span class="o">.</span><span class="n">get_ks</span><span class="p">(</span><span class="n">scsc</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="n">z</span><span class="p">,</span> <span class="n">threshold</span><span class="o">=</span><span class="mf">0.4</span><span class="p">)</span><span class="o">.</span><span class="n">ks</span><span class="p">)</span>
<span class="go">0.9</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">scks</span><span class="o">.</span><span class="n">drawks</span><span class="p">(</span><span class="n">scsc</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="n">z</span><span class="p">)</span>
</pre></div>
</div>
</div>
<div class="section" id="install">
<h2>Install<a class="headerlink" href="#install" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><code class="docutils literal"><span class="pre">python</span> <span class="pre">-m</span> <span class="pre">pip</span> <span class="pre">install</span> <span class="pre">ScoreCardModel</span></code></li>
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<p class="caption"><span class="caption-text">Contents:</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="ScoreCardModel.html">ScoreCardModel package</a><ul>
<li class="toctree-l2"><a class="reference internal" href="ScoreCardModel.html#module-ScoreCardModel">Module contents</a><ul>
<li class="toctree-l3"><a class="reference internal" href="ScoreCardModel.html#id1">评分卡模型</a><ul>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.html#id2">模块设计:</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.html#id3">依赖:</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.html#id4">使用方法:</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.html#id5">一个完整的例子:</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.html#id6">模型序列化</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="ScoreCardModel.html#subpackages">Subpackages</a><ul>
<li class="toctree-l3"><a class="reference internal" href="ScoreCardModel.mixins.html">ScoreCardModel.mixins package</a><ul>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.mixins.html#submodules">Submodules</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.mixins.html#module-ScoreCardModel.mixins.serialize_mixin">ScoreCardModel.mixins.serialize_mixin module</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.mixins.html#module-ScoreCardModel.mixins">Module contents</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="ScoreCardModel.models.html">ScoreCardModel.models package</a><ul>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.models.html#submodules">Submodules</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.models.html#module-ScoreCardModel.models.logistic_regression_model">ScoreCardModel.models.logistic_regression_model module</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.models.html#module-ScoreCardModel.models.meta">ScoreCardModel.models.meta module</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.models.html#module-ScoreCardModel.models">Module contents</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="ScoreCardModel.html#submodules">Submodules</a></li>
<li class="toctree-l2"><a class="reference internal" href="ScoreCardModel.html#scorecardmodel-discretization-module">ScoreCardModel.discretization module</a></li>
<li class="toctree-l2"><a class="reference internal" href="ScoreCardModel.html#module-ScoreCardModel.score_card">ScoreCardModel.score_card module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="ScoreCardModel.html#id7">评分卡</a><ul>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.html#id8">计算公式:</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.html#id9">使用方法:</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.html#ks">KS 曲线:</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="ScoreCardModel.html#module-ScoreCardModel.weight_of_evidence">ScoreCardModel.weight_of_evidence module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="ScoreCardModel.html#woe">计算Woe</a><ul>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.html#id10">触发概率</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.html#id11">woe</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.html#iv">iv</a></li>
<li class="toctree-l4"><a class="reference internal" href="ScoreCardModel.html#id12">使用方法:</a></li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
</ul>
</div>
</div>
</div>
<div class="section" id="indices-and-tables">
<h1>Indices and tables<a class="headerlink" href="#indices-and-tables" title="Permalink to this headline">¶</a></h1>
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<li><a class="reference internal" href="#">Welcome to ScoreCardModel’s documentation!</a><ul>
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